This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
8.7
Rating
0
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Machine Learning
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Excellent skill with comprehensive coverage of time series ML capabilities. The SKILL.md provides clear, actionable guidance with code examples for all major tasks (classification, regression, clustering, forecasting, anomaly detection, segmentation, similarity search). Structure is exemplary: concise overview in SKILL.md with detailed references properly delegated to separate files. Task knowledge is outstanding with quick-start examples, algorithm selection guides, and best practices. The skill addresses a specialized domain (time series analysis) that would require significant tokens for a CLI agent to handle independently, especially for algorithm selection and proper data formatting. Minor room for improvement in description clarity around when to choose this skill over standard sklearn for borderline cases, but overall this is a high-quality, well-structured skill that meaningfully reduces computational cost for time series tasks.
davila7
Skill Author
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